{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Examples and Exercises from Think Stats, 2nd Edition\n",
    "\n",
    "http://thinkstats2.com\n",
    "\n",
    "Copyright 2016 Allen B. Downey\n",
    "\n",
    "MIT License: https://opensource.org/licenses/MIT\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from __future__ import print_function, division\n",
    "\n",
    "%matplotlib inline\n",
    "\n",
    "import warnings\n",
    "warnings.filterwarnings('ignore', category=FutureWarning)\n",
    "\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "\n",
    "import random\n",
    "\n",
    "import thinkstats2\n",
    "import thinkplot"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Survival analysis\n",
    "\n",
    "If we have an unbiased sample of complete lifetimes, we can compute the survival function from the CDF and the hazard function from the survival function.\n",
    "\n",
    "Here's the distribution of pregnancy length in the NSFG dataset."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import nsfg\n",
    "\n",
    "preg = nsfg.ReadFemPreg()\n",
    "complete = preg.query('outcome in [1, 3, 4]').prglngth\n",
    "cdf = thinkstats2.Cdf(complete, label='cdf')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The survival function is just the complementary CDF."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "import survival\n",
    "\n",
    "def MakeSurvivalFromCdf(cdf, label=''):\n",
    "    \"\"\"Makes a survival function based on a CDF.\n",
    "\n",
    "    cdf: Cdf\n",
    "    \n",
    "    returns: SurvivalFunction\n",
    "    \"\"\"\n",
    "    ts = cdf.xs\n",
    "    ss = 1 - cdf.ps\n",
    "    return survival.SurvivalFunction(ts, ss, label)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "sf = MakeSurvivalFromCdf(cdf, label='survival')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.1397801412101171\n",
      "0.8602198587898829\n"
     ]
    }
   ],
   "source": [
    "print(cdf[13])\n",
    "print(sf[13])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Here's the CDF and SF."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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2Hapi2+4jkY1XVr/0Dg1NrXx6xXnaTjFFKdxFUlRBXhZz8sYxZ/o4ILTc8vd/9TyvbdgJwAtrttHY1MIdN1+oTdNTkH5liwwRfr+Pz93yQS5YfEbk2Bsbd/OtB56mqTm27Rdl8FC4iwwhaWlpfPqG8/jw+XMjxzZuL+PrP3qyz1srSnJTuIsMMWbGLVctYcWHFkaObd9zhK/831VU13Z/EVYGF4W7yBBkZlx3yTl8/OqlkWN7D1by5R/8kcrjdR5WJvGicBcZwi4/bw633bgsssbIgfLjfPkHqyivqvW0Ljl9CneRIW7Z4hnccetFpKWF4uBIZQ1fuveJPm1OIslH4S4iLJ0/hS/80yWRTUMqj9fzpXv/2OtiZpK8FO4iAsCCWRP54srLSA+Ebn+pqWvkyz9YxY695b18pSQjhbuIRMydUcJXP30FWZnpANQ3NvPNB56mqrre48qkrxTuItLBGZNH8/V/+TC52RlAqAf//V8+F9NG4pI8FO4icoopE4r4t3+8ODKLZvOOgzz2Zy30N5go3EWkS3Omj+Ojl51cfPDxv7x5yprxkrwU7iLSrWsvPpu500uA0EYN3//lc7rJaZBQuItIt9LS0vjXmz/I8PxsAGrrm/jeLzT+Phgo3EWkRwV5Wdxxy4WR8fetuw7xm6fWeFqT9E7hLiK9mjV1LCsuXxR5/ofnNrB+814PK5LeKNxFJCbXXDSfs84YH3n+w1+/QH2jlglOVgp3EYmJmfHZmy6IjL/X1DXy+F/e9Lgq6Y7CXURiVpCXxa1X/Y/I8ydf3MThozUeViTdUbiLSJ8sPXsK0yYWA9DW1s6vVr3ucUXSFYW7iPSJmXXY5OP1t3exZechDyuSrijcRaTPppeOYunZUyPP/98fXsU552FF0pnCXUT65aYPLyYQXv991/4KXly73eOKJJrCXUT6pXhEHsuXzYs8f/jJNTQ1t3pYkURTuItIv33kwrMYlheaGllVXc8fn3/b44rkBIW7iPRbVmY6N16xMPL8iec2aGGxJKFwF5HTsmzRDCaOLQSgpTXIw09q3ZlkoHAXkdOSlpbGP37k5I1NL63drmUJkoDCXURO25zp4xhTVACE1n2vPK49V70WU7ib2aVmts3MdpjZXd20+aiZbTGzzWb26/iWKSLJLj83K/K4tr7Jw0oEwN9bAzPzAfcBFwFlwFozW+Wc2xLVZhpwN7DUOXfMzIoTVbCIJKfcrIzI47oGDct4LZae+yJgh3Nul3OuBXgEuLJTm08C9znnjgE458rjW6aIJLu83MzI47oG9dy9Fku4jwOid8UtCx+LNh2YbmavmNnrZnZpV29kZivNbJ2ZrauoqOhfxSKSlPKyT/bca+oU7l6LJdyti2OdF5HwA9OA84EbgJ+Z2bBTvsi5B5xzC5xzC4qKivpaq4gksdyckz33eg3LeC6WcC8Dxkc9LwEOdtHmj865VufcbmAbobAXkSGiQ89dF1Q9F0u4rwWmmdkkM0sHVgCrOrV5AlgGYGYjCQ3T7IpnoSKS3KJ77rqg6r1eZ8s454JmdhvwDOADHnTObTaze4B1zrlV4dcuNrMtQBtwp3Ousq/FtLa2UlZWRlOTfuv3JDMzk5KSEgKBgNeliERE99w1FdJ7vYY7gHNuNbC607GvRD12wOfCH/1WVlZGXl4epaWlmHU11C/OOSorKykrK2PSpElelyMSkRfVc69Vz91zSXWHalNTE4WFhQr2HpgZhYWF+utGkk50uNep5+65pAp3QMEeA/0bSTLKy+l4QVU7M3kr6cI9Fa1atYpvf/vb/frar33ta3z3u9+Nc0Ui8Zce8OMP78zU1tZOc0vQ44qGtpjG3KV3wWAQv7/rf87ly5ezfPnyAa5IZGCZGXnZGRyraQBCF1UzM3TR3yvquXdSX1/P5Zdfzrx585g9ezaPPvoopaWlHD16FIB169Zx/vnnA6Fe9cqVK7n44ou5+eabWbx4MZs3b4681/nnn8/69et56KGHuO2226iurqa0tJT29nYAGhoaGD9+PK2trfz0pz9l4cKFzJs3j2uuuYaGhoYBP3eR05Wn6ZBJI2l77tfc/uOEvffj9/5zt6/9+c9/ZuzYsTz11FMAVFdX84UvfKHb9uvXr+fvf/87WVlZfO973+Oxxx7j61//OocOHeLgwYOcc845bNq0CYCCggLmzZvHiy++yLJly/jTn/7EJZdcQiAQ4Oqrr+aTn/wkAF/60pf4+c9/zmc+85k4nrVI4uVqOmTSUM+9kzlz5vDXv/6VL3zhC7z88ssUFBT02H758uVkZYWWOv3oRz/Kb3/7WwAee+wxrrvuulPaX3/99Tz66KMAPPLII1x//fUAvPPOO5x77rnMmTOHhx9+uMNfACKDRb6mQyYNhXsn06dPZ/369cyZM4e7776be+65B7/fHxlK6TwFMScnJ/J43LhxFBYWsnHjRh599FFWrFhxyvsvX76cp59+mqqqKtavX88FF1wAwK233soPf/hDNm3axFe/+lVNdZRBKfou1VotHuappB2W6WnoJJEOHjzIiBEjuOmmm8jNzeWhhx6itLSU9evXc9lll/H444/3+PUrVqzgO9/5DtXV1cyZM+eU13Nzc1m0aBG33347V1xxBT5faHZBbW0tY8aMobW1lYcffphx4zovvCmS/KLvUq3TVnueStpw98qmTZu48847SUtLIxAIcP/999PY2MgnPvEJvvWtb7F48eIev/7aa6/l9ttv58tf/nK3ba6//nquu+46Xnjhhcixb3zjGyxevJiJEycyZ84camtr43VKIgNGPffkYV7daLBgwQK3bt26Dse2bt3KmWee6Uk9g43+rSQZPff6Vn70mxcBOG/hdD57U2jYcdP+6kibOeN7vo4lPTOz9c65Bb2105i7iMRNXs7JfVTr6jUs4yWFu4jETYepkNpqz1MKdxGJGy0eljwU7iISN50XDxPvKNxFJG5ys06Ge31Ds1aG9JDCXUTixu/3RRYLc0B9Y4u3BQ1hCvd+yM3NjTy+8847mTVrFnfeeaeHFYkkj7zsqLnuGprxjG5iOk0/+clPqKioICMjo/fGIkNAbk4GFcdCN+HVNTQBmtfuBfXcu/DLX/6SuXPnMm/ePD72sY+xe/dulixZwsKFCzvcebp8+XLq6+tZvHhxZDEwkaGuY89dc929krQ99+g72uKtpzvkNm/ezDe/+U1eeeUVRo4cSVVVFbfeeiuf+tSnuPnmm7nvvvsibVetWkVubi4bNmxIWK0ig01eroZlkoF67p08//zzXHvttYwcORKAESNG8Morr3DDDTcA8LGPfczL8kSSXp7WdE8KCvdOnHNdbkCtTalFYpOrNd2TQtIOy3i1uNAHP/hBPvKRj3DHHXdQWFhIVVUVS5cu5ZFHHuGmm27i4Ycf9qQukcGiw7K/6rl7Rj33TmbNmsUXv/hFzjvvPObNm8fnPvc57r33Xu677z4WLlxIdXXirgWIpII89dyTQtL23L10yy23cMstt3Q49tprr0Ue33XXXZHHdXV1A1aXyGCQq557UlDPXUTiSj335KBwF5G4ytNuTElB4S4icZWrfVSTQtKFu1aR653+jSSZ5WZncGLicGNTC8Fgm6f1DFUxhbuZXWpm28xsh5nd1UO7a83MmVmv+/t1JTMzk8rKSoVXD5xzVFZWkpmZ2XtjEQ+YGTnqvXuu19kyZuYD7gMuAsqAtWa2yjm3pVO7POCzwBv9LaakpISysjIqKir6+xZDQmZmJiUlJV6XIdKtvJxM6sIXU0PryyTdIEHKi2Uq5CJgh3NuF4CZPQJcCWzp1O4bwHeAf+tvMYFAgEmTJvX3y0UkSZwyHTI928NqhqZYfp2OA/ZHPS8LH4sws/nAeOfck3GsTUQGqfycrMhjTYf0Rizh3tWiKpFBcTNLA74HfL7XNzJbaWbrzGydhl5EUlduTvTiYY0eVjJ0xRLuZcD4qOclwMGo53nAbOAFM9sDvA9Y1dVFVefcA865Bc65BUVFRf2vWkSSWvSa7nUN2mrPC7GE+1pgmplNMrN0YAWw6sSLzrlq59xI51ypc64UeB1Y7pxbl5CKRSTpdei516nn7oVew905FwRuA54BtgKPOec2m9k9ZrY80QWKyOBRUdvM5rJqjjUbDQRoIMB7FQ1elzUkxbRwmHNuNbC607GvdNP2/NMvS0QGo/LqJtodZGWlR441Np4clknTtggDRpNPRSRu2sNTLXKiwr2+KRTuaQbFBbr5bqBoyV8RibucrAyyaQUgPdjk2eY7Q5l67iISd1mZgcjjOs1z94TCXUTiLidLm2R7TeEuInEX8Pvw+ULx0hpso7ml1eOKhh6Fu4jEnZmRH71pR72GZgaawl1EEqLD4mENGpoZaAp3EUmIPPXcPaVwF5GEiA73Gl1UHXCa5y4ifVZR2xy5G7U70TNm6jUdcsCp5y4ifdZbsKcZ5Oeq5+4lhbuI9FlvwV5ckHnqbkwyoDQsIyKnpbulBTpcUNWwzIBTz11EEkI9d28p3EUkIdRz95bCXUQSIjd6qz313Aecwl1EEiIveqs99dwHnC6oikiXYpnL3pPotWXq6ptwzmGmrZgGinruItKlWIK9p23z/H4fGemhdd3bnaOhqaX7xhJ3CncR6VIswd7btnkdhma0vsyA0rCMiPSqv9vk5WZncvRYHRC+qDoyP55lSQ/UcxeRhMnX4mGeUbiLSMLkZGvxMK9oWEZkiDvdWTE9Uc/dO+q5iwxxsazw2F8d57or3AeSwl1kiItlhcf+ir5LVcMyA0vDMiIS0d9ZMd2J7rlrWGZgqecuIgmT2+EuVfXcB5LCXUQSJr/DJtnquQ8kDcuIDBGJnBXTneipkHUacx9QCneRFNPfED+dWTHdUc/dOzGFu5ldCtwL+ICfOee+3en1zwH/BASBCuDjzrm9ca5VRKLEsyd+urNiupOTlY4BDmhoaqGtrR2fT6PBA6HXcDczH3AfcBFQBqw1s1XOuS1Rzd4CFjjnGszsU8B3gOsTUbCIhPS3d15ckElRXkbvjeMgLS2N7KwM6htDQzJ1Dc0U5GUNyPce6mLpuS8CdjjndgGY2SPAlUAk3J1zf4tq/zpwUzyLFBkKEtETH6gQ70lezslwr6lvUrgPkFjCfRywP+p5GbC4h/afAJ7u6gUzWwmsBJgwYUKMJYoMDf0N9jSDWSXxnZ8eT8Uj8jl8tAaAbbsPM370cI8rGhpiGfzq6jJLlz+CZnYTsAD4z65ed8494Jxb4JxbUFRUFHuVIkNAf4M9EWPl8TR/5vjI4zUb93hXyBATS8+9DBgf9bwEONi5kZldCHwROM85pzlPMuSdzjBLvO8U9dLC2aX84onXANi4vYym5lYyMwIeV5X6Ygn3tcA0M5sEHABWADdGNzCz+cBPgEudc+Vxr1IkCQzUPPFETEn00piiAsaPHs7+w8doDbbx9rYyFs+d5HVZKa/XYRnnXBC4DXgG2Ao85pzbbGb3mNnycLP/BHKB35rZBjNblbCKRTwyUMGe7MMs/bFwdmnk8ZpNezyrYyiJaZ67c241sLrTsa9EPb4wznWJ9IkXd1/GIplmrXhp4ZxSfv/XtwBYv3kv7e3tpKVpvnsi6Q5VSQkDGezJPjslGU2bWMzw/GyO1TRQW9/Ett1HOHPKGK/LSmkKd/FUsva4u5OqwyaJZmYsmD2RZ1/dCoSGZhTuiaVwl7jyOqzVq05eC2eXRsJ97Tt7uPnK92GWYlePk4gGvSSuvA529aqT15zp48hID02BPFRRTdmR4x5XlNrUc5ceDURPXBcdh4b0gJ/5Z5Tw+sbdAKzdtEd3qyaQwn0IGcghEw2PSFcWzik9Ge7v7OHqi+Z7XFHq0rDMEDKQwa7hEenKObMmRtYzeW/PEY7XNnhaTypTz30I6W+wa9hE4iUvJ5Mzp4xhy85DOGDdO3u5cMmZXpeVkhTuQ1QqrV0ig8vCOaVs2XkICC0kpnBPDIV7CvJ6OqJIT7SQ2MDQmHsK6i3YU21hKhlcTiwkBkQWEpP4U899EOtPD10XOyUZLJozif2HjwGhu1W1SmT8KdwHgdPZzV7TESUZLZg9kceffRPQQmKJon/NQeB0NkIWSUYnFhIDqK1vYt3mfR5XlHrUc09JcJQAAAAIg0lEQVQipzPMommKMpiYGUvnT+XJFzcC8IsnXmX+GeMJBHweV5Y6FO5JJJYLoRpmkVRxzcXzef6Nd2loauHw0Rr+9MJG3bEaRxqWSSK9BbuGWSSV5OdmseJDCyPPf/eXN6mqrvewotSicE9Sc8YXdPiYVVKgoRdJOZcsnUnJqNC0yOaWVv77T294XFHqULh7oKK2mc1l1Wza3/FDZKjx+318/Jqlkecvrt3O9j1HPKwodSjcPaCbjEROmjejpMM895/97u84p9urT5fC3QMaWxfp6JarluD3h2bK7Nxfwd/e2OZxRYOfZsskUCxTG7WAlwiMKsznymXzIjc2/feTb/C+eZPJzkr3uLLBS+EeB6dzB6mIhFx90Xz+tmYbVdX1VNc28ttn1nPLVUu8LmvQ0rBMHOgOUpHTl5kR4JYrT4b5Uy9tiiwNLH2ncI+D3sbQRw/L1NRGkRgsPXsKZ0weDUBbWzv3/OhJNry73+OqBieFe5wpxEX6z8z49A3nMywvtO5Ma7CNbz3wNG+E912V2Cnc+0Dz00USb1zxML7x2eUUDssBQj347z74F15e957HlQ0uCvc+0Px0kYExtngY37z9KkaPzAeg3Tnu/dVzPPvqFo8rGzw0W6YL2gRDxHtFI/L4xmev5J77n2L/oSoc8ONHX6KhqZXly+Zipt5UT8yrO8EWLFjg1q1b58n37s3msmqtziiSJGrrm/jG/U+xc39F5NjYogIu+8Bsli2aQVbm0JoLb2brnXMLemsX07CMmV1qZtvMbIeZ3dXF6xlm9mj49TfMrLTvJScP3UEqkjzycjL52r98ODKLBuBgRTU/f/wV/ukrv+LB37/CoQpd++qs1567mfmA7cBFQBmwFrjBObclqs2ngbnOuX82sxXAR5xz1/f0vsnQc9cdpCKDR3NLK48+vY5nX91KQ1PLKa/PnDKGktHDGVWYz6jCfEaPDH1OtbtcY+25xxLuS4CvOecuCT+/G8A59+9RbZ4Jt3nNzPzAYaDI9fDmAxXu/b17FDT8IpKMmppbeWHNdla/tIkD5cd7bZ+RHiA94CPg95Ee8OH3+QgEfPh9oYGLE2P30WP4ZmAY0cP6aWmGLy0Nv8+Hz2f4fKH38PnSIu07fH3kfYk6bpF21116TmSrwb6INdxjuaA6Doi+i6AMWNxdG+dc0MyqgULgaGzlxm6gph5q+EUkOWVmBLj03Flc8v6ZbNx+gKde2MSbW/bSXf+tuaWV5pbWAa0xFh86b3a/wj1WsYR7V5ekO/87xtIGM1sJrASYMGFCDN868bQHqcjgZGbMm1HCvBklVFTVsvtAJUeO1lBeVcORo7UcPlrNkapagsE2r0vtUqJn+8QS7mXA+KjnJcDBbtqUhYdlCoCqzm/knHsAeABCwzL9Kbg/FOAiqa1oRB5FI/JOOe6co7GpldZgW+SjpbWNYLCNYFsb0QPHJ0aRXfTjyOfQ42BbO23t7QSD7bSdeNzWFvUeoXZdvm/4mAv3ewtys+J1+l2KJdzXAtPMbBJwAFgB3NipzSrgFuA14Frg+Z7G20+HLnCKSKzMLOUuqMaq13APj6HfBjwD+IAHnXObzeweYJ1zbhXwc+BXZraDUI99RSKLFhGRnsV0h6pzbjWwutOxr0Q9bgKui29pIiLSX1pbRkQkBSncRURSkMJdRCQFKdxFRFKQwl1EJAV5tuSvmVUAe/v55SNJwNIGSU7nPDTonIeG0znnic65ot4aeRbup8PM1sWycE4q0TkPDTrnoWEgzlnDMiIiKUjhLiKSggZruD/gdQEe0DkPDTrnoSHh5zwox9xFRKRng7XnLiIiPRh04d7bZt2pwMweNLNyM3sn6tgIM3vWzN4Lfx7uZY3xZGbjzexvZrbVzDab2e3h46l8zplmtsbM3g6f89fDxyeFN5l/L7zpfMqtV2tmPjN7y8yeDD9P6XM2sz1mtsnMNpjZuvCxhP9sD6pwD2/WfR9wGTATuMHMZnpbVUI8BFza6dhdwHPOuWnAc+HnqSIIfN45dybwPuBfwv9dU/mcm4ELnHPzgLOAS83sfcB/AN8Ln/Mx4BMe1pgotwNbo54PhXNe5pw7K2r6Y8J/tgdVuAOLgB3OuV3OuRbgEeBKj2uKO+fcS5y6k9WVwC/Cj38BXDWgRSWQc+6Qc+7N8ONaQv/jjyO1z9k55+rCTwPhDwdcAPwufDylzhnAzEqAy4GfhZ8bKX7O3Uj4z/ZgC/euNuse51EtA22Uc+4QhMIQKPa4noQws1JgPvAGKX7O4eGJDUA58CywEzjunAuGm6Tiz/f3gf8FtIefF5L65+yAv5jZ+vA+0jAAP9sxbdaRRGLaiFsGJzPLBR4H/tU5V5PoDYS95pxrA84ys2HAH4Azu2o2sFUljpldAZQ759ab2fknDnfRNGXOOWypc+6gmRUDz5rZuwPxTQdbzz2WzbpT1REzGwMQ/lzucT1xZWYBQsH+sHPu9+HDKX3OJzjnjgMvELreMCy8yTyk3s/3UmC5me0hNKR6AaGefCqfM865g+HP5YR+iS9iAH62B1u4RzbrDl9RX0Foc+6h4MQm5IQ//9HDWuIqPO76c2Crc+7/RL2UyudcFO6xY2ZZwIWErjX8jdAm85Bi5+ycu9s5V+KcKyX0/+7zzrl/IIXP2cxyzCzvxGPgYuAdBuBne9DdxGRmHyL02/7EZt3f9LikuDOz3wDnE1o57gjwVeAJ4DFgArAPuM451/mi66BkZu8HXgY2cXIs9n8TGndP1XOeS+hCmo9QJ+sx59w9ZjaZUK92BPAWcJNzrtm7ShMjPCzzb865K1L5nMPn9ofwUz/wa+fcN82skAT/bA+6cBcRkd4NtmEZERGJgcJdRCQFKdxFRFKQwl1EJAUp3EVEUpDCXUQkBSncRURSkMJdRCQF/X/v1ZXAilWYSgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "thinkplot.Plot(sf)\n",
    "thinkplot.Cdf(cdf, alpha=0.2)\n",
    "thinkplot.Config(loc='center left')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "And here's the hazard function."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.6767068273092369\n"
     ]
    }
   ],
   "source": [
    "hf = sf.MakeHazardFunction(label='hazard')\n",
    "print(hf[39])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "thinkplot.Plot(hf)\n",
    "thinkplot.Config(ylim=[0, 0.75], loc='upper left')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Age at first marriage\n",
    "\n",
    "We'll use the NSFG respondent file to estimate the hazard function and survival function for age at first marriage."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "resp6 = nsfg.ReadFemResp()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We have to clean up a few variables."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "resp6.cmmarrhx.replace([9997, 9998, 9999], np.nan, inplace=True)\n",
    "resp6['agemarry'] = (resp6.cmmarrhx - resp6.cmbirth) / 12.0\n",
    "resp6['age'] = (resp6.cmintvw - resp6.cmbirth) / 12.0"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "And the extract the age at first marriage for people who are married, and the age at time of interview for people who are not."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "complete = resp6[resp6.evrmarry==1].agemarry.dropna()\n",
    "ongoing = resp6[resp6.evrmarry==0].age"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The following function uses Kaplan-Meier to estimate the hazard function."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "from collections import Counter\n",
    "\n",
    "def EstimateHazardFunction(complete, ongoing, label='', verbose=False):\n",
    "    \"\"\"Estimates the hazard function by Kaplan-Meier.\n",
    "\n",
    "    http://en.wikipedia.org/wiki/Kaplan%E2%80%93Meier_estimator\n",
    "\n",
    "    complete: list of complete lifetimes\n",
    "    ongoing: list of ongoing lifetimes\n",
    "    label: string\n",
    "    verbose: whether to display intermediate results\n",
    "    \"\"\"\n",
    "    if np.sum(np.isnan(complete)):\n",
    "        raise ValueError(\"complete contains NaNs\")\n",
    "    if np.sum(np.isnan(ongoing)):\n",
    "        raise ValueError(\"ongoing contains NaNs\")\n",
    "\n",
    "    hist_complete = Counter(complete)\n",
    "    hist_ongoing = Counter(ongoing)\n",
    "\n",
    "    ts = list(hist_complete | hist_ongoing)\n",
    "    ts.sort()\n",
    "\n",
    "    at_risk = len(complete) + len(ongoing)\n",
    "\n",
    "    lams = pd.Series(index=ts)\n",
    "    for t in ts:\n",
    "        ended = hist_complete[t]\n",
    "        censored = hist_ongoing[t]\n",
    "\n",
    "        lams[t] = ended / at_risk\n",
    "        if verbose:\n",
    "            print(t, at_risk, ended, censored, lams[t])\n",
    "        at_risk -= ended + censored\n",
    "\n",
    "    return survival.HazardFunction(lams, label=label)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Here is the hazard function and corresponding survival function. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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yv0gBbT0HTftw8hfXvpwJ+yu7D3hbRK4RkauBGQQEkzSMcmOXx5TVUCLH+A5PVADvfpu0cAF4ZPo7kfv/7V3PZJxX+AiTsBrMth11PPfmApZ/Wt4JqtoD2U7+iBpMW3Hyp1HV60TkKeAop+jbqhr9F2MYLYDXV9LYmIQO0fpYt3EbDQ2NVFbudrx7w84UGjEgiPcXr2TLtp1NIWoqfMxFYZ3gdz/yBi+9vZCunTty57Xn0rlTxAdQAhZ/vJpPVq1n/EEjQ9+/DVrIil6m3KY2WopIhYi8r6pzVPVm58+Ei1GWrN+0jXcX1mT4Q7zLiQvVYG6897mM8ywBk+OHX7N6A5fd8G9+ffuT1O9qCKznZdmKdU3Hfma9sALmpbcXAqkxz3xvWej7l4r1m7bxiz8+xq0PvMyDT88K3a5d+GBaaBzNQV4Bo6pJ4F0R2asZxmMYBbN9Rz0/+s0Urr31CSZP2z2J1TdkTuiFbryc4eRBT7Njh1eDCZ4qPl27mY9XruOdBct57IV3m8oXLVvNq7MWZ5nx0rgFjB9+Wk058sRL85qEvvvz56OVfLyiyKfB7KzbxT8ee5N/PfE2u3Y1tioNJqyTfyAwX0TeBralC1X11FhGZRgF8OLbC5v8Ig9Pn8M5Jx8KZJvIGhqSTH3xXTZv2cHpxx+U4UjPhzvQ5PadHid/yB/++4tXcOZXDubTtZv5xU2PosA3N2z1rbts5ToeenYOCz/6lFF798+67qfB/OuJt3n9nWq+dcrhHDH2M9mfoQXemcNqIt7Jti1qMN7vST4L2cPPzmkSyt26dmL8QSPiGlrJCStgfhnrKAyjBHiXDafxboh8c+5S7v3Pm0AqvMv5px0R+h6NjckmP0wUE5mb9KQ55amZTVP9/U/M8K372pzqpvHP+eCT7L48AmZV7SYenj4HgN///VkevvkHWW1aYhVSWDGRPfm2nrf1uHjkud0eiX8/M9v3paFcCbUERVVf9vuLe3CGEYWgjJJen8cUlw9g6ovhzTWQ6c/xriILu98mvfQ2TH2vcPTy76dns/CjT5vO1wZoQq2FoLf7uCNVNydeDbItfTYvoQSMiBwuIjNFZKuI1ItIo4jkjbwnIhNEZKGIVIvI5T7XO4nIFOf6DBEZ5pT3FZEXnfvd4mlzsIi857T5kzivgyLSR0Smi8hi5989wnw2o+2QCHB4e538XsEQBXdfhWowabNWqfZ4/OKP/2k6DmNRagmtIOy+I69/LJlUnn39A869/O/cPqVtvNNGNZHla1/OhN0HcwtwNrAY6AJ81ykLREQSwF+AE4HRwNkiMtpT7UJgg6qOBG4CbnDKdwJXAj/16fo24CJglPM3wSm/HHheVUcBzzvnRjvCa69PT6ReH0wxZAoYrw8m3Jtoepgt5V5oERNZyM+aNfmi/PXBV9hZt4vpbyxgxZqNMYyuddGazIahtzOrajWQUNVGVf078KU8TQ4FqlV1qarWA5OBiZ46E9m9YfMh4FgREVXdpqqvkRI0TYjIQKCnqr6pqaf8D+A0n77udZUb7QTv8uMdjgAorYDZfY+dddkmsuqP1/Dj30zhd55Nkm7SgrAU0QRaDSEljFeD8U6mW7ZmTAmtEq8QjRrKqDUJmLBO/u0i0hGYKyK/BVYB3fK0GQwsd53XAIcF1VHVBhHZBPQFgiL4DXb6cfc52DneU1VXOX2tEpHsJTdGm6auPlOj2L6znq5dOrIrwr6TfOTUYBqTPPj0bGpWb2hKtexH2jTWHBqMX3rlcp6gvJNvodlI2zKt6YmEfYU616l7CallykOBr+dp4/fz8T6bMHWKqZ/dgchFIjJLRGbV1tZGaWqUCY+/OI8fXTeZl2cuyiiv96wiS8cKy6fBPPDk26Hv3dgY7INRYPYHH+fto8lEFkOcLW/SM798MS2xTDnsfp0sDcYz1rawajlro2VEn0o5vyB4CStgvgh0UNXNToTly4B987SpISWI0gwBVgbVEZFKoBewPk+f7ijO7j5XOya0tCltDT6o6h2qOk5Vx1VVVeX5CEa5sW1HHff85w1WrNnIn/75Qsa1Oo+mknbme538Xh56dg4bt2wPdf90X7t2Nfqu8OrauWPePtIaRRyTpXdMpYq7ViyF+mCeff0DTz+tX8KEFQ9bt9dlRNhuat965EtoAfNn4FUR+Zyr7No8bWYCo0RkuGNem8TufDJppgLnO8dnAC9oDvHsmMC2OKvaBDgPeMynr/Nd5UYbYtOWHb7lqpplskprGGFCs2zbEW5lWdoHs6POv/7Aql55+0ivIosjmZZXg/ETruUwQQUF3YwrtUI5ETZc/98eeo27H3k9b/tyJqyA+Qj4DvCQiJzplOX8dahqAymT2jPAAuBBVZ0vIteKSDoCwF1AXxGpBi7DtfJLRJYBNwIXiEiNawXaD4G/AdXAEuApp/x64HgRWQwc75wbbQw/YfHp2s1876r7muJtpWly8ufRYNzk+/GmJ2yvMGsaX4h7xfkO7hd3rdj8I6XAu6DhZ797iK3b67LqtYcU0N7HHyRUX529OKB96xEwYZ38qqpzRORo4AEROQxIhGg0DZjmKbvKdbwTONPbzrk2LKB8FrCfT/k64Nh8YzJaF3X1qeWpPbp15ovjRvn6U35397Ns2Jxt4tqxsx5VzbtZEVLhY+79z5u8NHMR3zrlUI49/HO+9dITeNBeGq8fyA9xJts4koW5fUSQGm/WqqUy2Eexq6GRp1+bzxknfD6jPJ8G0wYsZK1KQBRLWAGTXp21VkS+Qmq/StYkbxil5vGX3mtywvfq0SXLWayqLFvhv+hw+876wPAxXmo3bGna1X/rAy8HC5hdaQ0mQMCEMMfFOUk2NCQ959kCpiX8MmGd/PmEX7klIEu9wCTp0CHv+3ZGm1zn+SiHF4SwhA0V81XXcVJVf6aq7WgRv9FSuFd43Td1Bjs9AiPXj3P7zvrQofFfnJFpXgvqN23CCRIwYQRa2lHd0Fi6/TlpvMKjoTHpuzu+HPCTOa0pbEpjY5Jf/PE/XPC/9zDz/WWh23mffltWaMKGiqkSkd+LyDQReSH9F/fgDMNLviySblav2xJ6k+Vb7y719Os/0eUzkXlXsvmRnljj0CSyfDC+GkzpBVs+/ISJnzaST/iVUzbH59/6kEXLVrOzbhfX3/l06HamwWRzPylH/XBSkZWXkVolZhjNhshux32anfX+znZI5VIJM+H7EbSqrMnJv8P/vmGc1BVNGkzpBUwYDca70qw5CJssLd/zK6e3/VW1mwpql5XRMqLQbE0+nLACpq+q3gXsciIpfwc4PMZxGUYWFSJZpqnVa4Njri7/dH1WUjA3udL2bt2RvcIJ3KvICg+YmTaRNUZY3ZaP9KTjnaD9nPzNuVIrvazcV4PxKczn5G9Nb+9BZGswEduXkRaXj7BO/vTr2ioR+SqpzY1DctQ3jFjYWZepOdTmCE/f2JhkaY3/AoAB/XoyoF8v5n643Pf6Np8ltLBbQ/COIwoSgwaTzlPjNX/5+2CaR8DceO9zvD6nmlOPOZA+vbIjS/k5/vMJkLawTyZLg4kci6yEg4mZsALm1yLSC/gJqU2XPYH/jm1UhuHDkuW1WU70fBP9itX+0XcTFRUkcgSb3LzNP6hiKTSYZDLJmvVbmDU/f1iZsDQmk1SSyFpF1lIazKYtO3h9TjWQyrlzwWlHZtXxNZHlEX7lYB7asHk7f/zHc7y/2BuYJCxFajBl8AzCEkrAqOoTzuEm4Jj4hmO0N9as30LPbp1zmqvceINI5lu1tX7zNt/yikQFlZXBAub/7njKt7wUAqYxqdz6wEsFt/fts1GZ++FyXpjxYUb5g0/N4pNVmdGXmsMH8/HKdRnn/iay7LK8GkwZmMh+ffu0wKXxYSjWyd+K5EtuASMifyZH6BxV/VHJR2S0G16ZtYib73uB7l07cetV59CtS6fIfeRz4m/02YAJKQ2mkHD5DXlWkYVhxeqNRU1Qfiz6eDW/uu3JrPIly7MDuubTEopl7ofLs8bi52/x22iab2wtbSLbsm1n0f932SayqO1bj4TJ9wubBcx2/k51Haf/DKNgbr4vtdJ96/Y6Hp3+Tp7a/uTb5+K3wx9S2S8rA1Is56KhKRZZ4T6YUgsXgNsnvxK6rteMVmr8BJ0fhWgwLT25Lv7YN4ZuUUR12re0kI1CTg1GVdMJvBCRS93nhlFKNgQEscxHvtAs6zf5C5jKygSJAgRMUzTlEq4AKwVRtJKkRhMwW7btpH5XA317d486rN339BEcflpNXg2mhU1kpfh/z06Z3HoERlTCOvmhdeW5MVoZYUOJeMlnIvMmIUuTqBASBUQzTk8wcWsBUYkySUVZvbZyzUYuvf5BNKlcffHJ7DdqcP5GPvgJDj8nf7mvIiuFgCt2mXJLC9koWLgXoywoND5X2FhjXhKJCioT4eNHpXlhxofc//iMssmzkibKxBtlFdmf73+RxsYkSVV+d/ezhQwN8BdqrdHJXwoB5zWJxaHBlItWlM/Jv4XdmktXEUnvahNSEZZ7xjk4o/1QaG6UQgVMZaKCRKKwez7yXGH+ojiJMvFGWUVW48rb4hdeH1JLxT+qWcs+w/cMXDjhF56mECd/S0+cpbi/n5N/fvVKZr3/MccesS9D9twjZ/uW1uKikM8H06O5BmK0b/wmmzXrt+RtFzaYpd/9CtFgypUoE18UDSafCVJV+fkfHqFm9Qa+fNi+XHzOl3zrJXPEjMvor8w1mDgcBTvq6rnqz6lcjG/OXcrt13yz6D5VtSyyf5qJzCgLvBrMA9Nm8sNf3p+3XcEaTGVFQT6YciXKxJtMJlm0bDX3PPpG1n4VSE1Ob8xdwiuzFuUVRstWrGvam+Tdg+MmbIDNclqm3NDQyOvvLOG9RSuaykqxxNv7f1Xj2gxcuyH/S1WY/+tyUXJiFTAiMkFEFopItYhc7nO9k4hMca7PEJFhrmtXOOULnRw0iMg+IjLX9bdZRC51rl0jIitc106K87MZxeF94/YKmIeeCbcKftGy1VllYTZtVlRUkKhsOxpMlI2f9bsaueKmR3n8pXlNb85u5nzwCX/4+/SmZeRpOoR4XkGalJ8Pxm81WzktU37x7YXceM90rvnL4yz5pLbZ7x9EmDGUwzghRgEjIgngL8CJwGjgbFfa4zQXAhtUdSRwE6lEZjj1JgFjgAnArSKSUNWFqjpWVccCBwPbgUdd/d2Uvu5k0zTKFO9yz0JNH34Ta89unfO2SyQKW0XWFtjoWhLu51f5wz3P+bbr1DHbou59MQhaxvvky+9llfnNgXl9MM1oIrt9yu69RX99MHVcinnbO/lH/e6Xi/AIQ5wazKFAtaouVdV6YDIw0VNnIpDeW/MQcKykDIcTgcmqWqeqHwHVTn9ujgWWqGrpAjoZzYbXtOX2pRT7A+rcqQOVed62KxOF7YOJi44douwYKA5vWuXsCc9/kk8LmJfeXshFV9/H/Y/PaMrwmSYozYEffhNr2S9TzrGHKOz3ttjPEKZ1ucigOH9hgwF3qNoap8y3jqo2kIp11jdk20nAA56yS0RknojcLSK5l2IYLYpXwLjffIvdzFZRUUGPrrnDzlSIlJWTv2OElLvF4k3C5p3UgybATo4Q/PP9L7Ju4zYeee4dVqzJDCa6LSDNgR9+E3K5riJLa2q5BGChY9OIfp1QJrIy2bYYp4Dxsz94P3VQnZxtRaQjqdA1/3Zdvw0YAYwFVgF/8B2UyEUiMktEZtXWZsdpMpoHb6Iw96TnTSoWlUSF0COPmazcnPxh/BulwvvsvZN6kBmqY8ds35Y3WvX2CBqM3zxZrvtg0suvc83tubKruilWSJaLdhKGOAVMDTDUdT6EVB4Z3zoiUgn0AtaHaHsiMEdVmzy8qrpaVRtVNQncSbZJLV3vDlUdp6rjqqqqCvpgRvHU1Xk0GJeAyZWlMgyJREVeAZOoKM0y5QoRLj332KL7aU5z3U7Ps9+weXvGpBc0AXbwiT69eVtmiJ+gvTJ++Jmb8u3Raak383SkiVwCLuwKM+/jjWoyMyd/ipnAKBEZ7mgckwDvkpWpwPnO8RnAC5p6MlOBSc4qs+HAKOBtV7uz8ZjHRGSg6/R04P2SfRKj5Hj3V7jNYsUk84KU8PAKGO/KskSHtyTSAAAgAElEQVRFuI2WQwf24XtnHBV8r0QFR40bxVEHjypssA6FBN4slHqPAP+va//FZTf8u2lJctDU5DdnbdmamTcnymo2fx9M7kk6rJZQappMZDl8MOEFTPyhYspEvsQnYByfyiXAM8AC4EFVnS8i14rIqU61u4C+IlINXAZc7rSdDzwIfAA8DVysqo0AItIVOB54xHPL34rIeyIyj1TOGkuIVsZ4hUh9w26BU7SJLCH06JbpgxnUv3dWnVwJx9L07tGFCUeNCbyeNm31652dsTEs+392cKixlAq/ueeTVet5c+7SnO38lhp7E7MVayLLq8G00MyZ3rOY20QWUsCEqVMuEqJIYl264iwVnuYpu8p1vBM4M6DtdcB1PuXbSS0E8JafW+x4jWxUle076wvK1TLng094/s0FHD9+NGP3HZpxLcvJ7zKRFZPMC1LaSc9uXTLKBvXvxVJXbpSwq8g6Vub+iaT7KGRPzSlfOoA+vbsx/qAR/Pr2ll9Vv2lr7ojW3tVnkIq07Ca9nDcMfqahfBpMS8276UgTuU1khflg/PrMJWDCmNTKRUA139pIo9Whqlx765O8t6iG8087klOOOSB022QyyXV/TU2ab837iIdv/kHGdW+U4/qG0vpguns0GG98JxF/v0eFSMYP2M/v4Cb9Qy7ESb/3oL4cc9g+TWNuafJ9hjAaTBT8V5HlnhjjTpYWRNpElssHFFqD8cYi8wl+2eIhcUpEy3+rjbJl8cdrmLeoBgXu+c8bkdp6E3I1eJYeZ2swu893Fr2KrIIeXTN9MJ8dtmfGeWNjMsssNaiqF7/96dczyjqE3J+Sb3Ie0C87Lqzb79KcPpgg8gqYhmSWUNhUYB4fCHhzj2Aia8639DDLlAv1wfhrMDnamw/GaAtEWRHkxbvhzrv3YmeOfTDFZIuE1DLlDp59JSP3ylwx2JhUKj3ayaD+veno2a2eb9JNTw5eAdHdsw/nuktPy2pbkSFgWn5PTr54YQ2NjZECZebj/idmMHt+5j7pMCay+l0N/O/N/+H71/zTN1RQHAghBEyIZ6OqvDRzUWY7z2dubEwWvVquPeyDMVo5xezN8Oas926ezHLy7yqdgKlIVNDPk33R60NKJjVLg+nQoTJLUIR9Bt56P5x0NP379KB7107ccNnXfPtx78MpNHVAKamrb+Dh6XMCrzc0JktuovrNHU9lnOczkSVVmfriPD5c+inrNm7zjaUWlTXrt/gG/XQTykQWQrOY+2ENr8+pzmznEUyquQVZ1IykLYn5YIxAvHGmooQA92ow3mXJuQTMzhI4+fcZvidHHjSC+dUr+cFZR2fVaUwms/weHSorsoROvh326WnAK5gG9OvJrVedQ0NDkg4dElkCF8gIZ+O972UXHM+N90zPee9Ss7O+gQeefDvwemNjMvZlwvk3WiZZ8smapvNioz6sWLORH183GQX+58KvcNgBw33rhTGR5dO+IKW1efEKpqRmmyLdhDF/lYuJzASMEYj3x1RX3xAqUjFkrwTz5m3ZURes4RRtIktUICL85ILjA4ViYzKZJRR6de+SpWnkixGWfkbedl06d0Rkt6kuaEFBGq+JbMzIgd7qsZNLuEDq/yjuWGD53s5Lff/bJ7/c9JLw27ueyVqMkib9Hco18RdqPvQKJtXcn9M2WhptAu+qoSgT/zaP/8YbFNG7mzyZTNLYmGRn3a5IARP9cE/cQRqXn5O/b+/uWX4Z73kQCU+9rp07Bo6pqW+3D8bTvjn3xYQlpcHEa57JpyGVet7cvDXcKrj09yjXxF+o+dD7IteYTOZ28peH7AiFaTBGIF6nb5Qd9vk0GL++pjw1i0emzynaPRlGKDQmNUuD6dO7W2QfTPpN0auBdPFGDvDRYNxl3lTD5ShgkqqhE4cVfo88GkxLL1MuMBZZ6gXK/7rXRKaaWwNpTRqMCRgjkIaGzB9zFAGTbxWZ10QG5HQwRyHM5NzYmO2D6de7W5agSJvIjjp4FK/OXpzVT/qH7J34vOkCRFLrkNw/e/c4vYItrObU3Hj/H0tNPg2mpcL1pzXQXEuEgzSYDZu3c/mNj6S0c5+Vmd52yXwaTIhXsDKRL2YiM4LxmkOiCBivUztbgyks1fHXjjuII8aOyFknjIDx22jZt3f3rIUN6b6+ffqR9O/TI6uf9O/YK4x97+kZl1uoeMfiZ1IrB7z/j6UmnwApduL8dO1m/v3MbD5euT5Su91O/hyxyALMh3/796us3bCVrdvrfEVD0mcVWS4hUi7CIwwmYIxAvCt0IvlgPHlBfnPHU1x/59NNE1ShAS2HDNiD/n2656zjFRJpzj31cCCVC+KsEw/J+qH27tEly2eT7qtXjy5cffEpWX2mNZgwq5m86QHcQsW7T6ccdvb74d0gW2ry7oMpYof7qtpN/PwPDzN52kx+ddsTzgKQcG2bnPw56vgtU378xXm8Ne+jnH1n7YNJJovOO1Mu+2DMRGYEkrV3JUIIl+0+u/Fnvr+MB56cyfmnHeFrIgtDoqIi79t9UJ6Xk4/en6o+PdizTw8G9OuZlSzLLwum+1a5wsb075ut3XhJ+VkaPecpTjhyNG/PW8byT9dz6XnHhl4Ongsh9ZmKXcrrJm4Bk3cfTBE+mMdemNu0eXjD5u2pl5yQz7nQcP1hImB4zYL5BEhrWqZcnq9JRlngdeimc7i8/s4SLrr6Pu56+LXAttsDMhtOffFdZ7VY4ROV1yF+7/99O1S7ysoE4w8awci9+wMwuH9vDj9gOBUVFVxw2pEB99o9AfktWU7/kEePGMgXDh5Jz+5d+Nl3TvDtK1uDcW+0rODqi0/mzmvPZb9R3uSt2QSNN83oEQO59epvcue1pY0BG7uJLG8+mMJZs25L5r0iONLTcij3PpjMMDZzP1weWDdzHF4fjOYUEOHC9ZeHhDENxgjEu0w5vTIsvQFw2ivvc9wRn2PvQVnBrX01mDRr1m8pfK+LQIVn13sx6YZ/duFXqKvfRSefbI2wO4ou+K8oS6e7FRH++7zjcm5GDfLvuAmruYzauz+fGVqVESE6o+9Eha/PqFi8G2ZLTT4NpZAgkNt21NGpQ6WPMz24L69PLT1fhw12+f7ilfzqtidDjS9Lg6F8BESxmIAxAslaReZjIluzfouvgPHbuZ5m2Yp1RZk6vCayYgNFBgkX8JrI8guyXAIiaylyEeOuqJCce1LOOOHzBfedC+9+plJT6pTJz77+AXc8+AqD99yDLp0z/59z7VvJEkbOhB9mo6Wq8qvbwwkXd99N53nD5YSLeVYOmInMCCTIROYm6Hucy1b/+78/G+r+P5x0NH+84qyMMhHxccRXZNUpFe6+EokKvjI+M/lYlJ+x10RWjGAUCV61dMk5x4QysxVCHD6YbTvqWLRsdagw9VGc17Xrt/DXB19BgZrVG1j88ZqM68mkEvRN8Wrv6ReiXMuo00Lp1gdejrQh1Vs3tUy5bYSKiVXAiMgEEVkoItUicrnP9U4iMsW5PkNEhrmuXeGULxSRr7jKlzmZK+eKyCxXeR8RmS4ii51/MxOAGJHxajBRHPPFhnsB2LNvT4YOyP5vzPd2VkoB443KfNE3gtMn5yOMiSyI7GXMFYGr5dI5ZtJccdGJoe+TxhuJIE0cAuZH103hipseZfJTs/Luho+iwbyRJ0NnlMjIYUxkyaRS/fEaXpjxYegxQra2pBQfKqZciE3AiEgC+AtwIjAaOFtERnuqXQhsUNWRwE3ADU7b0cAkYAwwAbjV6S/NMao6VlXHucouB55X1VHA8865UQReDSaXX8VLLhNZWPr6pCEWCZ85sFBO+uJ+AOzRsyuH7jcs6/qpxxzYdHzKl8InYfOa2KKYyDp5FhhUVAg/nJQdxNOPcWP25uZfnEXP7l3y1q3aowf/99+nB2YwjcMHs3HLdgAeemZ2SUxkO+t28cJbHzJ/8cqc9XIJM+93P5SJLJnkmdc/yDu+rHZZGoyWQIMpDyEUpw/mUKBaVZcCiMhkYCLg/h+YCFzjHD8E3CKp18+JwGRVrQM+EpFqp783c9xvIvAl5/he4CXg56X4IO0Vr5lg67adWT8G7/myFWt5452loZfGjv/8SN79cLlv7pl+e2TvdxEkdv3/gtOOZNx+wxg+uK/v0uVvTDi4abzfmDAu63oQ3kk7iomsU8fKjPA7IilH/7X/36lMf2OBb5QBN0P23IP+fXqwOUda5CPGjuCy84+loqIiMJLArpid/Hk1GM29yx3gn4/P4KlX3897ryjpj9N1c5nIGhqSrFm/Oe99s8bh44MJ0k4h5E7+yKOIhzgFzGDAvU6vBjgsqI6qNojIJqCvU/6Wp23aqKzAsyKiwF9V9Q6nfE9VXeX0tUpE+vsNSkQuAi4C2GuvvQr8aO0Dr4lsy/a6LMGxq2H3hJNMJvm/O59m7Yatofo/6Yv7cdaJh3DZDQ/6CpigSMb5JphiLWSJRAUH7jMk8HqXzh25+JwvRe63Z/fMLJu5JhEvnTyJ0ERSEaPHjBzExi078goYyK0x/fKSUxgzclCTeTFI+D30bGnC+QSR1wcTYuYMI1wgjwbj+Z6nVwvmzgeTe4NkENk7+ZMkk8H/V2WinIQiTh+M36/H+2iC6uRqO15VP0/K9HaxiHwxyqBU9Q5VHaeq46qqqvI3aMd4hcmWrTv4YMmqjDJ3bKqt2+tCCxeASScdQveunTKWAqc5+pDP+rbp3rVTiwU8LJbunjTOUTQYr7B1C6ewYWVybRT9zJAqz4KGlsmwWUofTD6iaDDps3z7Uwox33pbpO7RNoJdxilgaoChrvMhgNco2lRHRCqBXsD6XG1VNf3vGuBRUqYzgNUiMtDpayCQuWTEiIzXDr2ydhPX/XVaRlldfQPJZJI/3/8il17/YM7+vBNh2pHszeb48+9O4Adn7X5vOG/iEQiwz/AB7DdqUH71v0zjePXolmkii7IYIVuDiX7/XIsKvHuJcgmjOMm/RDf7+rsLa3jq1fcjhx/KveTY44NJ+gc1zWiTTJbk5aexsQShYspDvsRqIpsJjBKR4cAKUk77czx1pgLnk/KtnAG8oKoqIlOBf4nIjcAgYBTwtoh0AypUdYtzfAJwraev651/H4vxs7ULdoUI4Fi/q4HpbyzgpbcX5q0rFQIuG3Z6gvUKnkP3H5ZxPvHLB3L0IaPo1T0VK6yUb7HNiXdlVjECxv3MwpravJGiM655fE256sZJPg3GL37Ytbc+AcCGTds55+RDfVoF3MtnKXEymaSioiLLPNwkYHLM3KmU0sV/N5W24+SP7TVFVRuAS4BngAXAg6o6X0SuFZFTnWp3AX0dJ/5lOCu/VHU+8CCpBQFPAxeraiOwJ/CaiLwLvA08qapPO31dDxwvIouB451zowi8b3F+rFm/hcdfmpe33leP3j9wQj1+/O7FheM/P9K3Tu8eXUNlFSxnugaszApDpw6ZmwTdz3K/UYOajnP5jqKkACjFMvNCKGYVWdR0D8mkZgmZ9MKW7I2W6U2UuforTUK2ZDL3fqByCWQZhlh38qvqNGCap+wq1/FO4MyAttcB13nKlgIHBtRfBxxb5JANF95VZH48m2dZZq8eXfjWyYdx5EEjAuue+IX9WLZiHVu31XH+xMPz3jNuJ39cdO0cLt10mp7duzSt+jpw3yHM/uDjpmtuh323Lp34zaWn8d7ilXzZswfGjXdDai4G9O3BshVrI423FOQzMW3fUZ/xHIq6l2rWd7yhIUnHDtnf/fR3Lp/fphT5akoRrr9cXsIsVIwRSJgcJ/kYPWIQXz58XyDYJNShQ4IffevLofsMEyqjHImqwVz5g5O497E32WfYAA7cN1Mz8T7JfYYPYJ/hA3L2F2VRwSnHHMjyTzcweM/edOvaiRdn5DeBloJ8GkyphAukTGReP2N6YYvf3hTYvZrMj2RjMmtFWEHjSiapqAg2UYYL118emIAxAilFetzOnXZ/xUq1wz6vBhMYAKRlCdodH8Rnhlbxy0tS1uRVtZsyrhXyLKOYyPb9zAD+9L+TAPjn1Lfy1C4dhea1TxPlzT2pmuVnTH/ns0LFpE1krrKffvsEPl27iX8+PgNIjb3Y8QN5Q+aUi3YSBotFZgRSijwi7tz0pTJd5Q8VU5r7lJq9B/UpuK1X+4iyhyaoj7B0CNiPlLddiOCgXopdwBHlO5tMatZ+l0AfTNMqMvcilUxTZWOj5k35HAbV3N/xMGa4chFCJmCMQLxvcX476/Phzvvi9g/kS3uci3yTa9UepQ9TXwr69OrGf519NGP3HcovL8nOjpmLrFhkBQiYKLHP3BQiKE47dmykKAdpitUAogiYxmQy2wfjnHvNwx8sWcX7i1dkCJiKioqMZ9qYTJbEfJvU3L4cC3ZptAncP77f/+wMbr/6m5H7GDZ4dyj/SScdwoH7DGH0iIF852u5E2bl4vTjDmpyWJ91YmoSu+yC4+lQmWDU3v05+pBRBfcdN8ce/jmu/OFXI0c79mofhZgBCxFKED3fzoihVZx76uFZS6vD0OwaTJaT3/HB+Ai6q295PMP5XlEh2QKmBMuUc8Ui05R6U/Q9mgvzwRiBNLp+rB07Vka2+x88em+OOnj3suNuXTpx1X+dXPS4+vTqxm9/8jVWrNnIYfsPB2D8QSMYN2YvOnaIPs7WQCk0GC/Dh/Rj5ZpNXHpe7sWXQSF78lHIGP3e3E8/diyPPj83VPv6CPlqGhqzN0am890ELTd2T/xC5ibhxhLtg0mF6/d/9w8rX8rFRGYCxgjE7QCNar//wVlf5PgjvcGzS8fwIf0YPqRfRlmuxGGtnVL4YLxzzu9++nV2NTTmFSCFZgwtxCTnndjHjBzE6JGDQguYKBqMX/rnzdt2cv/jM5izwD/dcW4TWfa+mkLIFa5fNfcmzN31ih5GSTABYwTiXkUWVcB06RRtxZSRG+9kXYiJzGu+EZFQ2kmhTv5ChKA76On//ffpjNyrincXrgjdvj5Cvhq/7JzeUEhe3BN/RYV4nPylWUWWz0QWTjspDwljPhgjkJ2uH2su7eDwA4Zz2AHDM8o6R9xUaOQmDhNZWApx8kP4IJxBDNlzDyoqghOr+bFtR3ZU7iAKSZ6WZSLz+GBKs5M/2JeT1Na0j98EjBFAQ0NjU9IwAbp1CdZI9v/sELp49ni4lycbxeP1KxXiTC50aorqrE/fJUpCNT/S/o0ogmrbjvCJ7gpJntboiaVX4fLBJBuTJdnJn8yhpeRbwry7XnmIIRMwhi/uH2q3rp1yOs6PPmQUPbtlhqLfo2fX2MbWXtl7UGpF3oB+PelSgIZY6KTTUhpMOo1DFA1mewQB4+eDyYfbx5O9ikxLspM/FSom4Foyf8K1dB/lgPlgDF82b9vZdNzDIzzc/Pf5x9Glc0eOPmQUL81cRF19AycfvT+D+vdujmG2K6743gTefHcph+w3rKCVcoUuoe1YoICRIs14aQ0mymf1S1wXhJ8PJh9uoVQhmT6YhsbGkpivNEewS6V8tJMwmIAxfNnm+qF277o7htaIoVUsWV4LwNlfPZQvONGPhw3ux9+vO98Jp972lgmXA1V9enDqMb6xXkNR6LzUIeIqsvQEWOjGzjRB6RxysTWCDyZq9GXIzHQpIhljK0XkC0inhW4bwS7NRGawfUd91hdyy3Z/DebS845l1N79GTdmb0495oCsvky4tD2acx+MmyYBE8lEFl7AFIJ76X5FhWSsroyyBycX+cL1h4kWUCbyxTSY9s7r7yzh5vueZ1BVL3730zOa3la3bvPXYAb17831l32t2cdpFE+hDuhCfTDu700xRHlniWIiS3P6sWOZs2A5H69cl7eue+m+10RWKgGTL1x/mHhnpsEYZcGN90ynsTHJ8k838PRr85vKgzQYo/VS6KRT6EbLfYcP4AsH+yeQi0La2R+GKE5+SJl8v3Xq4aE/o1uIiGQ6+b2BMwslZSLLfb21EKuAEZEJIrJQRKpF5HKf651EZIpzfYaIDHNdu8IpXygiX3HKhorIiyKyQETmi8iPXfWvEZEVIjLX+Tspzs/WFllZu7HpOEiDMVovp3xpt0nzuCM+F7pdVBNZegVhIlHBf593HD//7oRI7b1E2wcTTcB8fsxeQPgU0d5VZO6xFbIqzY9kUtFcic3CaDBlslsmNgEjIgngL8CJwGjgbBHxxg65ENigqiOBm4AbnLajgUnAGGACcKvTXwPwE1X9HHA4cLGnz5tUdazzl3tLbjtHVfnNX5/KKHO/nbk1GBMwbYPhQ/px2QXHc9aJ4/jWKYeFbhfGRHb591JCJJGo4HtnHpVxrXhfTPi6UTZawm7BEjZXToNHwLh9MKVy8ufb6xImWkCZWMhi9cEcClQ7aY4RkcnARMCdN3cicI1z/BBwi6Q8exOByapaB3wkItXAoar6JrAKQFW3iMgCYLCnTyMEb8xdmpUd0P0D2bzVZSLraiaytsL4g6KnSQizYfKQ/YZxy/87m66dO9KrR5eMa8Xuh5EIJrKVnsRs+UgLz7ChkDL9WPH4YJJ5Ui+XImJzcxGniWww4I4YV+OU+dZR1QZgE9A3TFvHnHYQMMNVfImIzBORu0VkD79BichFIjJLRGbV1tZG/Uxtho9XZDs03W9nazdsbTru07tbs4zJaN0MrOqVJVyg+JWFUTSgqH6QtGAJayJzkzKRuQVMiUxkeZYpW8KxFH7fCu+nDqqTs62IdAceBi5V1c1O8W3ACGAsKS3nD36DUtU7VHWcqo6rqqrK/QnaMH7q/Ix5H7Fo2WoA1qzf0lS+Z9+ezTYuozwZM3JQ03FUcVGsiSxq+yir3tJ1Cwlr4/XBlMzJn9TcTv4QGkyZyJdYBUwNMNR1PgRYGVRHRCqBXsD6XG1FpAMp4XK/qj6SrqCqq1W1UVWTwJ2kTHSGw866XRlvWEFvW1fc9CjPv7WAzVt3AKmQ5H16WdiX9s6Pz/0yF5x2JDdd/g0m/+F7fHbYnqHbFm0iC1mvQ2WCk48+gFuvOoeuncNF824ykYX0wXjH5V5FVqo5XTX3SjFvDptyJk4fzExglIgMB1aQctqf46kzFTgfeBM4A3hBVVVEpgL/EpEbgUHAKOBtxz9zF7BAVW90dyQiA1V1lXN6OvB+TJ+r1fFRzVr+9+bHSFQIv/vZGQzo15PV6zYH1r/1gZebjqv26J5hBjDaJ317d+cUn421YSjVhstcXPj18Rx/xOimfVwdOiRgZ55GuH0w0U1kIhI5jUUYUsEuc1xvRT6Y2ASMqjaIyCXAM0ACuFtV54vItcAsVZ1KSljc5zjx15MSQjj1HiTlvG8ALlbVRhH5AnAu8J6IpDMQ/cJZMfZbERlL6kViGfD9uD5ba+Pm+56nrn4XAH+d8gpHjP0M7wQkVPJS1ad7nEMz2gHFajBhzFeHH/iZjJA2Yc1kiSYfTHRBkUhESyUQllzh+iHsKrLyEEKx7uR3Jv5pnrKrXMc7gTMD2l4HXOcpe40AjVlVzy12vG2RNeu3sPzTDU3niz5ezbxFNaHb9+9j/hejOIp18ncKkxTNI1DCBuhMC6VCBIzXRFYqcoXrh5A+mFIOqAgsVEwb5pHp73D/EzMyyqK+2Awf0reEIzLaI8W+5YfJR+OtUxlWwBRpIis2540fqX0wwdfDOfnLQ8SYcb0N4xUuEH0z2JiR3pXlhhGNQkxk48bs3XQcJoyLV4MJayJrWqZcgJPfu9GyVCSTydxOfgsVY7Q0QW8wUVeg7DXQdzuRYYQmqgaz36hBfP+sL7raV+TVFLxmuLD3jLrR0nuPWHwweZz8FuzSaHGixmTy46wTx1n4faNook7C555yOH16ZW7uDeOHcRPWdJUWLIWYugSJxQejmtsMFm6jZSlHVDgmYNoo6zZuzV8pB/sMH8A3Jowr0WiMtkaUF4+oLymdOmWng44acDPsxF9ZhA8mLg1Gk5onXL+ZyIwWxh3qpRBsebJRKqLuo/Jz6odx9LsJLWCK9MGISMn3iSWT+cL1m4nMaGHWbdxWVPti9y4YbZvTjxvbdPzVo/fPWTfqV6mzjzCJmpMmkYjfByPOjolEibWYpGpOX6ktUzZanHwmssMPGM5b8z4KvG6+FyMX48bszUVnHsWGLdsz8sz4EfVlpXMrMpGl/q0AShOHDPIvUw6z0bJcMAHThlhVu4mb7n2O1es2B6aO7d61E7//2RlU9enBNy67I9CeO6CfbbA0ghERvvKFMaHrRsFviXGHyBpMOAFTlAbjfKySazB5wvXnSkbWVMdMZEap+fczs1myvDZQuPTo1pnfOcIFsn/4l11wPBUi9O3djVOPOTD28Rrtg6grtPwEkkSM4RzWL1KUD0YKX4GWi6Qmc5rILOGYETuqSjKpTV9uVQ2ML9a1c0dG7tWf73x9PP0d4QJwwpGfY9orqZigxxy2D+MPGsF+IwfRrUvH0DuhDSMfLeHPi7oPJlHQTv7Uv6XebFmacP3lIWFMwLRCPliyil/d9iQD+vXkyh9+lT69urFsxbqmEPtuKisT/OP6b/u+FU466RDWb9xGY1I579TDAXwTRhlGMZRCvuTqw+9SWLNV+gUtSg6ZNLt9MKUVoKlw/cUFuywXTMC0QiZPm0n9rgY+WbWe7111Hx0qE4EhYAb07RloA+/WpRM/u/ArcQ7VMGJP95DwEQ5RzVaFCIn076rUmy2Tmsxp4zINxigIVeWtdz8iqcph+w+jsjLB+k3bmPneMsaMGsQH1atYs24z86sz87blii82sKpX3MM2jJzEbSLzM1HFscPejeASMOVoIivheIrBBEwZ8fqcJdz0j+cAGNy/N+efdgSTn5rF0uW1Bff5hc+PLNXwDKMg4tjt7qYUAibqCN1WgdJrMHn2wZSJdhKGWMW8iEwQkYUiUi0il/tc7yQiU5zrM0RkmOvaFU75QhH5Sr4+RWS408dip89wOVPLiFdmLW46XrFmI7+546mChEuPbp0BGD1iIOM/P6Jk46dNlv0AAAu2SURBVDOMcsRvD4t3o2WpRZy4hGYcPphcIiRMqJg2byITkQTwF+B4oAaYKSJTVfUDV7ULgQ2qOlJEJgE3AGeJyGhS2S3HkEqZ/JyIfNZpE9TnDcBNqjpZRG53+r6t1J9r2Yq1/OaOp0rdLQAbNm0PXbdXjy784nsncvmNj2R8GYfsuQe//vFEFiz9lAM+O9g2TBotTim+g7n68FtinF5C3HSeqChpDC+32a/0JrLcGS1bU7DLOE1khwLVqroUQEQmAxNJpUFOMxG4xjl+CLhFUt+kicBkVa0DPnJSKh/q1MvqU0QWAF8GznHq3Ov0W3IB09CQLDoMSz4G9OvJiL368/qc6qxrJx61H5+u3cRZJ45j5N79ufNX5/H3R9/gg+qVjNq7P6cdO5Ye3Tpz6P7DYh2jYYQl7nccXxOZR4OpECnhXvt4TWSLP16TM3JBXX1D3j6efX0+c0OkRT9zwsHs0bNrpPFFIU4BMxhwf8Ia4LCgOqraICKbgL5O+VuetunMV3599gU2qmqDT/1WRSJRwTcmjOOL40ax18A+THlqVpM99vvf+CInjB+dUX+Pnl257PzjWmKohtFsdO0cbPHu2qVTVpk33Ez3rp3YsDnYQhB135fEqMGsqt2U83qYnE5Be+K8nHT0fq1WwPi9t3gVt6A6QeV+/5O56mcPSuQi4CKAvfbay69KTvYe1Jfbr/5m5HZh6d61E12cH9MZJ3yeU760Px07VNLYmLTNj0arpFuXTowYWsWS5bXs/9nBNDQkWbB0lW/dn393gm/5eRMPZ9b7y3x/1Jec86WsspO+uD//ef5d6up3ccZXDmbsPkP4f396LKOOO0jnmBED6du7W2jrxH4jB2UcL/zo01Dt2htxCpgaYKjrfAiwMqBOjYhUAr2A9Xna+pWvBXqLSKWjxfjdCwBVvQO4A2DcuHGRLZUdOiSaQq00B506pt7ETLgYrZmrLz6Z9xat4MB9hqAK8xbV0LVzR1au2cTYzw1l+4466uob2PczA3zbD+rfm5uuOIsNm7ax96C+fPjRp3SoTNC3dzf2HtQ3q373rp344xXfYPmq9YzddyiJRAW//cnX2dXQSFWf7iytWctB++6eSiorE/z2p19n0bI1jBk5kLkf1qBJ5aDRQ5lfvYpuXTqyfNUGFKVbl44cuv/wprZpc3U6wOyIoVX06dWNpTVrqagQunbuyNbtdYik0mj07N6Fzh0r6dK5IyvXbGRXQyOViQoG77kHn6xcn5ELZuiAPahdv5VuXTvR2Jhk45aUFlYhwl4D+/DJqvWowt6D+rDFdY+w9O4Rn/YCIHGtNnAExiLgWGAFMBM4R1Xnu+pcDOyvqj9wnPxfU9VviMgY4F+k/C6DgOeBUaQ0Fd8+ReTfwMMuJ/88Vb011xjHjRuns2bNKu0HNwzDaOOIyGxVzZuRMDYNxvGpXAI8AySAux1BcC0wS1WnAncB9zlO/PWkVo7h1HuQ1IKABuBiVW0E8OvTueXPgcki8mvgHadvwzAMo4WITYNpDZgGYxiGEZ2wGoyF6zcMwzBiwQSMYRiGEQsmYAzDMIxYMAFjGIZhxIIJGMMwDCMW2vUqMhGpBT4G+pHarNmaaI1jhtY5bhtz89Eax90axwzFjXtvVa3KV6ldC5g0IjIrzJK7cqI1jhla57htzM1Haxx3axwzNM+4zURmGIZhxIIJGMMwDCMWTMCkuKOlB1AArXHM0DrHbWNuPlrjuFvjmKEZxm0+GMMwDCMWTIMxDMMwYqFdCRgRuVtE1ojI+66yPiIyXUQWO//u0ZJj9CNg3NeIyAoRmev8ndSSY/QiIkNF5EURWSAi80Xkx0552T7vHGMu92fdWUTeFpF3nXH/0ikfLiIznGc9RUSC00I2MznGfI+IfOR61mNbeqxeRCQhIu+IyBPOedk+Zzc+4479WbcrAQPcA3hT5l0OPK+qo0jlnbm8uQcVgnvIHjfATao61vmb1sxjykcD8BNV/RxwOHCxiIymvJ930JihvJ91HfBlVT0QGAtMEJHDgRtIjXsUsAG4sAXH6CVozAA/cz3ruS03xEB+DCxwnZfzc3bjHTfE/KzblYBR1VdI5Z1xMxG41zm+FzitWQcVgoBxlzWqukpV5zjHW0h9sQdTxs87x5jLGk2RTmPYwflT4MvAQ055uT3roDGXNSIyBPgq8DfnXCjj55zGO+7mol0JmAD2VNVVkJpggP4tPJ4oXCIi8xwTWtmYmryIyDDgIGAGreR5e8YMZf6sHfPHXGANMB1YAmx0UohDKg15WQlL75hVNf2sr3Oe9U0i0qkFh+jHH4H/AZLOeV/K/Dk7eMedJtZnbQKm9XIbMIKUeWEV8IeWHY4/ItIdeBi4VFU3t/R4wuAz5rJ/1qraqKpjgSGkUo1/zq9a844qN94xi8h+wBXAvsAhQB9SmWrLAhE5GVijqrPdxT5Vy+o5B4wbmuFZm4CB1SIyEMD5d00LjycUqrra+YEmgTtJTSplhYh0IDVR36+qjzjFZf28/cbcGp51GlXdCLxEyofUW0TSadGHACtbaly5cI15gmOmVFWtA/5OeT3r8cCpIrIMmEzKNPZHyv85Z41bRP7ZHM/aBAxMBc53js8HHmvBsYQmPUk7nA68H1S3JXBs03cBC1T1Rtelsn3eQWNuBc+6SkR6O8ddgONI+Y9eBM5wqpXbs/Yb84eulw8h5csom2etqleo6hBVHQZMAl5Q1W9Sxs8ZAsf9reZ41pX5q7QdROQB4EtAPxGpAa4GrgceFJELgU+AM1tuhP4EjPtLzrJCBZYB32+xAfozHjgXeM+xswP8gvJ+3kFjPrvMn/VA4F4RSZB6aXxQVZ8QkQ+AySLya+AdUsKzXAga8wsiUkXK9DQX+EFLDjIkP6d8n3Mu7o/7WdtOfsMwDCMWzERmGIZhxIIJGMMwDCMWTMAYhmEYsWACxjAMw4gFEzCGYRhGLJiAMYwIiMjpIqIism+J+71URM4rZZ8h71slIk83932N9oEJGMOIxtnAa6Q2rJUEZxf4d4B/larPgHtkoaq1wCoRGR/XvY32iwkYwwiJE6NsPKlw7JNc5RUicquT1+QJEZkmImc41w4WkZdFZLaIPOOJCpDmy8AcVW0QkREiMsfV9ygRmZ2rLxH5nojMlFRulYdFpKtTfo+I3CgiLwI3iMjRrtwf74hID+c2/wG+WfonZrR3TMAYRnhOA55W1UXAehH5vFP+NWAYsD/wXeAIaIpr9mfgDFU9GLgbuM6n3/HAbABVXQJskt3Jn74N3JOnr0dU9RAnt8oCMvORfBY4TlV/AvwUuNgJMHkUsMOpM8s5N4yS0q5CxRhGkZxNKrghpIIGng3MAb4A/NsJhvmpozEA7APsB0xPhXsiQSoas5eBZCaC+hvwbRG5DDiLVBDCXH3t54Qp6Q10B55x9fVvVW10jl8HbhSR+0kJpRqnfA0wKMJzMIxQmIAxjBCISF9Spqz9RERJTfAqIv+Df8h2nPL5qnpEnu53AJ1d5w+Tijf3AjBbVdeJyKAcfd0DnKaq74rIBaTi1qXZlj5Q1etF5EngJOAtETlOVT907r0DwygxZiIzjHCcAfxDVfdW1WGqOhT4iJT28hrwdccXsye7J/iFQJWINJnMRGSMT98LgJHpE1XdSUoLuY1UGPV8ffUg5ajvQA5fioiMUNX3VPUGUmax9Eq4z1JGUYuNtoMJGMMIx9nAo56yh4FznH9rSE3SfyWVBXOTqtaTEkw3iMi7pCLWHunT91PAFz1l95OK3vwsQJ6+rnTuOR34MMdnuFRE3nfa73DuC3AM8GSOdoZREBZN2TBKgIh0V9WtjintbWC8qn4aof2jwP+o6mLn/KdAL1W9Mp4RZ9z7FWCiqm6I+15G+8J8MIZRGp5wEmh1BH4VRbg4XE7K2b/YETYjSPl8YsXJB3KjCRcjDkyDMQzDMGLBfDCGYRhGLJiAMQzDMGLBBIxhGIYRCyZgDMMwjFgwAWMYhmHEggkYwzAMIxb+f+9afyOxR+ywAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "hf = EstimateHazardFunction(complete, ongoing)\n",
    "thinkplot.Plot(hf)\n",
    "thinkplot.Config(xlabel='Age (years)',\n",
    "                 ylabel='Hazard')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sf = hf.MakeSurvival()\n",
    "thinkplot.Plot(sf)\n",
    "thinkplot.Config(xlabel='Age (years)',\n",
    "                 ylabel='Prob unmarried',\n",
    "                 ylim=[0, 1])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Quantifying uncertainty\n",
    "\n",
    "To see how much the results depend on random sampling, we'll use a resampling process again."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "def EstimateMarriageSurvival(resp):\n",
    "    \"\"\"Estimates the survival curve.\n",
    "\n",
    "    resp: DataFrame of respondents\n",
    "\n",
    "    returns: pair of HazardFunction, SurvivalFunction\n",
    "    \"\"\"\n",
    "    # NOTE: Filling missing values would be better than dropping them.\n",
    "    complete = resp[resp.evrmarry == 1].agemarry.dropna()\n",
    "    ongoing = resp[resp.evrmarry == 0].age\n",
    "\n",
    "    hf = EstimateHazardFunction(complete, ongoing)\n",
    "    sf = hf.MakeSurvival()\n",
    "\n",
    "    return hf, sf"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "def ResampleSurvival(resp, iters=101):\n",
    "    \"\"\"Resamples respondents and estimates the survival function.\n",
    "\n",
    "    resp: DataFrame of respondents\n",
    "    iters: number of resamples\n",
    "    \"\"\" \n",
    "    _, sf = EstimateMarriageSurvival(resp)\n",
    "    thinkplot.Plot(sf)\n",
    "\n",
    "    low, high = resp.agemarry.min(), resp.agemarry.max()\n",
    "    ts = np.arange(low, high, 1/12.0)\n",
    "\n",
    "    ss_seq = []\n",
    "    for _ in range(iters):\n",
    "        sample = thinkstats2.ResampleRowsWeighted(resp)\n",
    "        _, sf = EstimateMarriageSurvival(sample)\n",
    "        ss_seq.append(sf.Probs(ts))\n",
    "\n",
    "    low, high = thinkstats2.PercentileRows(ss_seq, [5, 95])\n",
    "    thinkplot.FillBetween(ts, low, high, color='gray', label='90% CI')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The following plot shows the survival function based on the raw data and a 90% CI based on resampling."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ResampleSurvival(resp6)\n",
    "thinkplot.Config(xlabel='Age (years)',\n",
    "                 ylabel='Prob unmarried',\n",
    "                 xlim=[12, 46],\n",
    "                 ylim=[0, 1],\n",
    "                 loc='upper right')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The SF based on the raw data falls outside the 90% CI because the CI is based on weighted resampling, and the raw data is not.  You can confirm that by replacing `ResampleRowsWeighted` with `ResampleRows` in `ResampleSurvival`."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## More data\n",
    "\n",
    "To generate survivial curves for each birth cohort, we need more data, which we can get by combining data from several NSFG cycles."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "resp5 = survival.ReadFemResp1995()\n",
    "resp6 = survival.ReadFemResp2002()\n",
    "resp7 = survival.ReadFemResp2010()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "resps = [resp5, resp6, resp7]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The following is the code from `survival.py` that generates SFs broken down by decade of birth."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "def AddLabelsByDecade(groups, **options):\n",
    "    \"\"\"Draws fake points in order to add labels to the legend.\n",
    "\n",
    "    groups: GroupBy object\n",
    "    \"\"\"\n",
    "    thinkplot.PrePlot(len(groups))\n",
    "    for name, _ in groups:\n",
    "        label = '%d0s' % name\n",
    "        thinkplot.Plot([15], [1], label=label, **options)\n",
    "\n",
    "def EstimateMarriageSurvivalByDecade(groups, **options):\n",
    "    \"\"\"Groups respondents by decade and plots survival curves.\n",
    "\n",
    "    groups: GroupBy object\n",
    "    \"\"\"\n",
    "    thinkplot.PrePlot(len(groups))\n",
    "    for _, group in groups:\n",
    "        _, sf = EstimateMarriageSurvival(group)\n",
    "        thinkplot.Plot(sf, **options)\n",
    "\n",
    "def PlotResampledByDecade(resps, iters=11, predict_flag=False, omit=None):\n",
    "    \"\"\"Plots survival curves for resampled data.\n",
    "\n",
    "    resps: list of DataFrames\n",
    "    iters: number of resamples to plot\n",
    "    predict_flag: whether to also plot predictions\n",
    "    \"\"\"\n",
    "    for i in range(iters):\n",
    "        samples = [thinkstats2.ResampleRowsWeighted(resp) \n",
    "                   for resp in resps]\n",
    "        sample = pd.concat(samples, ignore_index=True)\n",
    "        groups = sample.groupby('decade')\n",
    "\n",
    "        if omit:\n",
    "            groups = [(name, group) for name, group in groups \n",
    "                      if name not in omit]\n",
    "\n",
    "        # TODO: refactor this to collect resampled estimates and\n",
    "        # plot shaded areas\n",
    "        if i == 0:\n",
    "            AddLabelsByDecade(groups, alpha=0.7)\n",
    "\n",
    "        if predict_flag:\n",
    "            PlotPredictionsByDecade(groups, alpha=0.1)\n",
    "            EstimateMarriageSurvivalByDecade(groups, alpha=0.1)\n",
    "        else:\n",
    "            EstimateMarriageSurvivalByDecade(groups, alpha=0.2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Here are the results for the combined data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "PlotResampledByDecade(resps)\n",
    "thinkplot.Config(xlabel='Age (years)',\n",
    "                   ylabel='Prob unmarried',\n",
    "                   xlim=[13, 45],\n",
    "                   ylim=[0, 1])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can generate predictions by assuming that the hazard function of each generation will be the same as for the previous generation."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "def PlotPredictionsByDecade(groups, **options):\n",
    "    \"\"\"Groups respondents by decade and plots survival curves.\n",
    "\n",
    "    groups: GroupBy object\n",
    "    \"\"\"\n",
    "    hfs = []\n",
    "    for _, group in groups:\n",
    "        hf, sf = EstimateMarriageSurvival(group)\n",
    "        hfs.append(hf)\n",
    "\n",
    "    thinkplot.PrePlot(len(hfs))\n",
    "    for i, hf in enumerate(hfs):\n",
    "        if i > 0:\n",
    "            hf.Extend(hfs[i-1])\n",
    "        sf = hf.MakeSurvival()\n",
    "        thinkplot.Plot(sf, **options)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "And here's what that looks like."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "PlotResampledByDecade(resps, predict_flag=True)\n",
    "thinkplot.Config(xlabel='Age (years)',\n",
    "                 ylabel='Prob unmarried',\n",
    "                 xlim=[13, 45],\n",
    "                 ylim=[0, 1])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Remaining lifetime\n",
    "\n",
    "Distributions with difference shapes yield different behavior for remaining lifetime as a function of age."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of complete pregnancies 11189\n",
      "Number of ongoing pregnancies 352\n"
     ]
    }
   ],
   "source": [
    "preg = nsfg.ReadFemPreg()\n",
    "\n",
    "complete = preg.query('outcome in [1, 3, 4]').prglngth\n",
    "print('Number of complete pregnancies', len(complete))\n",
    "ongoing = preg[preg.outcome == 6].prglngth\n",
    "print('Number of ongoing pregnancies', len(ongoing))\n",
    "\n",
    "hf = EstimateHazardFunction(complete, ongoing)\n",
    "sf1 = hf.MakeSurvival()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Here's the expected remaining duration of a pregnancy as a function of the number of weeks elapsed.  After week 36, the process becomes \"memoryless\"."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "rem_life1 = sf1.RemainingLifetime()\n",
    "thinkplot.Plot(rem_life1)\n",
    "thinkplot.Config(title='Remaining pregnancy length',\n",
    "                 xlabel='Weeks',\n",
    "                 ylabel='Mean remaining weeks')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "And here's the median remaining time until first marriage as a function of age."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "hf, sf2 = EstimateMarriageSurvival(resp6)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "func = lambda pmf: pmf.Percentile(50)\n",
    "rem_life2 = sf2.RemainingLifetime(filler=np.inf, func=func)\n",
    "    \n",
    "thinkplot.Plot(rem_life2)\n",
    "thinkplot.Config(title='Years until first marriage',\n",
    "                 ylim=[0, 15],\n",
    "                 xlim=[11, 31],\n",
    "                 xlabel='Age (years)',\n",
    "                 ylabel='Median remaining years')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "## Exercises"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "**Exercise:**    In NSFG Cycles 6 and 7, the variable `cmdivorcx` contains the date of divorce for the respondent’s first marriage, if applicable, encoded in century-months.\n",
    "\n",
    "Compute the duration of marriages that have ended in divorce, and the duration, so far, of marriages that are ongoing. Estimate the hazard and survival curve for the duration of marriage.\n",
    "\n",
    "Use resampling to take into account sampling weights, and plot data from several resamples to visualize sampling error.\n",
    "\n",
    "Consider dividing the respondents into groups by decade of birth, and possibly by age at first marriage."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "def CleanData(resp):\n",
    "    \"\"\"Cleans respondent data.\n",
    "\n",
    "    resp: DataFrame\n",
    "    \"\"\"\n",
    "    resp.cmdivorcx.replace([9998, 9999], np.nan, inplace=True)\n",
    "\n",
    "    resp['notdivorced'] = resp.cmdivorcx.isnull().astype(int)\n",
    "    resp['duration'] = (resp.cmdivorcx - resp.cmmarrhx) / 12.0\n",
    "    resp['durationsofar'] = (resp.cmintvw - resp.cmmarrhx) / 12.0\n",
    "\n",
    "    month0 = pd.to_datetime('1899-12-15')\n",
    "    dates = [month0 + pd.DateOffset(months=cm) \n",
    "             for cm in resp.cmbirth]\n",
    "    resp['decade'] = (pd.DatetimeIndex(dates).year - 1900) // 10"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "CleanData(resp6)\n",
    "married6 = resp6[resp6.evrmarry==1]\n",
    "\n",
    "CleanData(resp7)\n",
    "married7 = resp7[resp7.evrmarry==1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Solution goes here"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Solution goes here"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Solution goes here"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Solution goes here"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Solution goes here"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.6"
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 },
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